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Record W2130276110 · doi:10.1109/isvlsi.2006.1

A "Soft++" eFPGA Physical Design Approach with Case Studies in 180nm and 90nm

2006· article· en· W2130276110 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsUniversity of British Columbia
FundersCMC Microsystems
KeywordsComputer scienceApplication-specific integrated circuitPlace and routeBenchmark (surveying)Physical designField-programmable gate arrayDesign flowEmbedded systemOverhead (engineering)Computer architectureSet (abstract data type)Integrated circuit designSoft errorElectronic engineeringComputer hardwareCircuit designEngineering

Abstract

fetched live from OpenAlex

Our recent work in embedded FPGAs has been focused on a soft IP approach where programmable fabrics are described at the RTL level and implemented using the ASIC digital flow and generic standard cells. Early results showed significant penalties in area, delay, and power overhead. However, using tactical standard cells and a structured physical design approach within such a flow, we were able to obtain large savings in area and delay. We defined this new approach as soft++ eFPGA. This paper provides details of the physical design flow, with particular emphasis on floor-planning, interconnect-planning, and clock tree synthesis. The advantages of our approach in handling larger circuits are demonstrated on a set of realistic benchmark circuits implemented in 180nm and 90nm CMOS process technology

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.612
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.244
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations19
Published2006
Admission routes2
Has abstractyes

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